Performance Analysis of the Network Selection Algorithms in ‌5G Heterogeneous Wireless Networks

Vertical handover is the essential feature of the next generation heterogeneous wireless networks. Network selection among accessible candidates is the most critical step in vertical handover procedure. Although various algorithms for network selection have been proposed, due to different approaches and diversity of parameters corresponding to this complicated problem, no unified benchmark or global indicator exists to evaluate the performances. In this paper, we define a global performance indicator (GPI) which comprehensively considers all subscriber satisfaction factors to assess users’ quality of experience (QoE). Our method is inspired by “Analytic Hierarchical Process” (AHP) and systematically utilizes both customer and network side parameters. This idea was led to propose a novel “automatic context-aware network selection” (ACANS) algorithm. ACANS is a “network-assisted”, “user centric” approach which dynamically and automatically affects customer context in the decision of the best network. A practical simulation platform evaluates and compares ACANS to well-known network selection algorithms such as SAW (Simple Additive Weighting), MEW (Multiplicative Exponential Weighting), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and TRUST (TRigger-based aUtomatic Subjective weighTing). Simulation results show that the proposed algorithm is compatible to customer preference and has superior performance in “No. of handovers”, “user’s volume of download”, “consumed energy” and “service cost”.